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Good data, bad side-effects

10. Nov 2017

Ths blog was first published in the Trendradar 2030

Data for development – the collection, allocation and use of data for development aid (DA) – has in recent years become progressively more relevant. Regardless of whether static or dynamic, whether produced by the public sector or by private corporations, this data is being viewed increasingly as the pivotal success factor in the struggle against all that is wrong with the world. But the data itself comes with its own moral dilemma: the majority of people aren’t able to use it, and the power of its interpretation rests in the hands of only a few major players. The question is whether that will change by 2030, and what we need to be doing in the meantime.

Is data the new Messiah?

What’s clear is that placing blind faith in data for the development, management and evaluation of development aid projects is of little use, since many of the data sets consulted for DA purposes are, for example, of poor quality or insufficient in their depiction of reality. Yet the bulk of digital data is growing daily, and it would be reckless to underestimate its mounting relevance for development aid. Digitisation has set off a veritable explosion of digital data, making it available and searchable in quantities and at speeds never before seen. Whether it be natural disaster preparedness, climate protection, or the fight against epidemics, there’s hardly an area of development aid that isn’t steeped in buzzwords like ‘big data’, ‘open data’ or ‘thick data’. Meanwhile, behind the hype, numerous global initiatives are pressing ahead with various approaches to effective and sustainable use of these troves of data, and attempting to coordinate everything amidst a sea of actors. The Global Partnership for Sustainable Development Data (GPSDD), for instance, is developing collective strategies for data usage, the International Open Data Charter (IODCh) is advocating to make as much non-personal data as possible accessible to everyone, while the Open Data Barometer (ODB) is measuring advances in the dissemination of data by governments around the world. At conferences, representatives of governments and development banks are debating and adopting resolutions, capacity-building programs for statistical agencies in developing nations are being launched, and the World Bank and its like are recruiting young, well-educated computer scientists to glean new insights from vast databases. 

Mere access to data will not lead to a better world

But will this new resource of digital data also benefit the intended recipients of international development aid? How can the world’s poor in so-called developing nations profit from it, when it’s only with adequate expertise, resources, and of course access to technologies, that this data can be put to sensible use? Multinational corporations, large international non-governmental organisations and development banks continue churning out applications, blinking dashboards and sophisticated analyses. But these are often based on data accessible only to certain users or in exchange for fees. It’s true that for some years now the growing open data movement has been advocating that everyone have free access to non-personal data sets, and has convinced even heavyweights like the World Bank to make their internal stores of data publically available. But it’s becoming apparent that mere access to data doesn’t lead to a more just, democratic and better world. For most of those seeking to use this new data to give the weak a stronger voice, lack of expertise and financial resources, as well as limited capacities, are proving to be often insurmountable hurdles.

When the global community convenes in the year 2030

And so this brave new world of digital data in development aid continues on a trajectory where there are indeed many people producing the data, but only a few who are making use of it. Even if, for the most part, those few mean well, a critical question is raised: how can we ensure that the existing power structures and their related inequities in DA and the developing nations are not being bolstered and exacerbated in the process? 20 years ago, the same positive potential was being attributed to the Internet as is being attached to the data revolution today. Access to the Internet was believed to be the key to setting free the democratising forces that would attest to the web’s enormous wealth of information and to the new possibilities for interconnection across borders. Along with all that was positive, however, the web also introduced new forms of privilege and discrimination, or actually made existing forms worse. Jobs are being lost to automation, user privacy is under threat, and hatred and harassment are nearly impossible to contain. So when the global community convenes in the year 2030 to discuss whether and how they’ve achieved the 17 goals for sustainable development adopted in 2015, it will be possible to see what impact the data revolution has had on developing nations. How, then, will data have been produced, used, and disseminated? By whom, and for what purposes?

Algorithms allocate funds for development aid

Let’s assume the current trends continue. A glimpse into the corresponding hypothetical future reveals what could await us in 2030: the data revolution, once heralded by some as a democratising force, will have given rise to an even more unjust distribution of resources and power. With the help of the private sector’s data giants, capable essentially of defining consumer behaviour for entire populations, DA organisations will have been able to design systems that shape and plan their projects and programs down to the last detail, controlling implementation and measuring effectiveness in real time. Probability calculators will be able to warn against armed conflicts and natural disasters before humans have a clue they’re coming. Specially developed algorithms will be able to improve the allocation of funds and goods for development aid in real time by drawing on a variety of indicators measuring economic development right down to the level of the individual household. Arguably, some portion of this data will owe its accessibility to the open data movement. But the infrastructure and expertise needed to make use of the data will remain out of reach for most people. And even in 2030, political will and economic strength will still be required to convert these data analyses into concrete measures. Data alone doesn’t change anything. Even if accessible to everyone, more data alone will not lead to greater fairness, participation and sharing. Currently it looks as if the opposite is more likely to be the case. But what can be done about it?

Requiring that data serving the common good be made public

More development aid funding has to be spent to strengthen the capacities of local civil society and media organisations, so that they will be capable of handling the growing volume of data. As critical intermediaries, these organisations must also be able to provide the public with clear, comprehensible and context-specific information and insights derived from this data. There also has to be a legal framework in place to set boundaries for the collection, use and dissemination of data. Especially where personal and individual-specific data is concerned, there must be cross-border regulation – allowing for specific national peculiarities – of what’s permitted. For example, telephone connection or Internet-usage data could be declared individual property, and regulations adapted to the digital age could help authorities collect census `data more efficiently. Data that serves the common good, such as traffic and health data, could be declared part of the public domain. Once it had been aggregated and made anonymous, those entities responsible for collecting the data would then be obliged to make it available to the public, even if it would no longer be to their exclusive economic advantage to do so. It’s becoming altogether clear that redistribution, a more just distribution of the power to access and utilise data is urgently needed. Only then can the data be used in the service of equitable participation, allowing its full democratising potential to be realised, particularly with regard to development aid.

This blog is a part of the November 2017 series on data for inclusive business.

Read the full series for insights on how the data revolution could affect inclusive business. Will it bring an end to the uncertainty of business in Base of Pyramid markets? Can it straddle the development-business divide? Will the data drive spurred by the Sustainable Development Goals be useful to inclusive business?